Look, I'm not even mad that your dataset is the spaghettiest of all spaghetti, but why do you have ten different jupyter notebook files lying around?

I mean, I'm not implying that a monkey has more brain in his armpit than you have in your entire body, but like, you call this a dataset while all over seen so far is half-processed garbage. You could've just dipped your pc in sewage and the results would still be cleaner than this.

Luckily, your paper is half decent so what the hell, let's see if I can fish anything useful out of this. But I swear to god if I come across another static path in this... And here we go! Another static path! Ladies and gentlemen, I propose we get this guy's phd back until he learns to fucking do a decent code.

(It's actually a massively complicated project, so it kinda makes sense to be this big of a mess. But still!)

Cousins came over...

Me: just compiling some python code, opens up jupyter notebook to take a look at some data science code
Little Sis: *looks at jupnb dump on cmd*
Whoa are you Hacking?
Me: yeah. I got bored of whole Hacking command typing thing so I opened up my hacker console.
*print("hello world")*
Sis:wow!
Me: you know what, typing is too tiresome, I'll connect to it with my mind
*alt-tab*
*cmatrix -b*
*sits in yoga pose*
Little Sis: Screams at the top of her lungs and runs to aunt
"DAVE IS HACKING MATRIX"

To all the data engineers in here: WTF is going on in your field?

I've worked closely with a dozen data engineers in the last 5 years (and talked to friends and internet strangers about this and get similiar responses), mine if them seem to know how to use a computer!

They don't understand git, ORMs, best practices, how to use a terminal, DAGs (important for using modern ETL scheduling tools like airflow and prefext), etc

Guys with 10 years of experience on their resume and they can't wrap a model into a flask app with 1 endpoint. They'll reference local files on their machine in w jupyter notebook and are shocked it won't work on other computers!

I decided to learn Swift as I would like to make apps. So I installed swift and swift-jupyter in my Linux server after my 2012 iMac literally took 20 fucking minutes to compile `print("hello world")` in Playgrounds. Meanwhile, my server compiles python code in a swift jupyter notebook in seconds.

python machine learning tutorials:
- import preprocessed dataset in perfect format specially crafted to match the model instead of reading from file like an actual real life would work
- use images data for recurrent neural network and see no problem
- use Conv1D for 2d input data like images
- use two letter variable names that only tutorial creator knows what they mean.
- do 10 data transformation in 1 line with no explanation of what is going on
- just enter these magic words
- okey guys thanks for watching make sure to hit that subscribe button

ehh, the machine learning ecosystem is burning pile of shit let me give you some examples:

- thanks to years of object oriented programming research and most wonderful abstractions we have "loss.backward()" which have no apparent connection to model but it affects the model, good to know
- cannot install the python packages because python must be >= 3.9 and at the same time < 3.9
- runtime error with bullshit cryptic message
- python having no data types but pytorch forces you to specify float32
- lets throw away the module name of a function with these simple tricks:
"import torch.nn.functional as F"
"import torch_geometric.transforms as T"
- tensor.detach().cpu().numpy() ???
- class NeuralNetwork(torch.nn.Module):
def __init__(self):
super(NeuralNetwork, self).__init__() ????
- lets call a function that switches on the tracking of math operations on tensors "model.train()" instead of something more indicative of the function actual effect like "model.set_mode_to_train()"
- what the fuck is ".iloc" ?
- solving environment -/- brings back memories when you could make a breakfast while the computer was turning on
- hey lets choose the slowest, most sloppy and inconsistent language ever created for high performance computing task called "data sCieNcE". but.. but. you can use numpy! I DONT GIVE A SHIT about numpy why don't you motherfuckers create a language that is inherently performant instead of calling some convoluted c++ library that requires 10s of dependencies? Why don't you create a package management system that works without me having to try random bullshit for 3 hours???
- lets set as industry standard a jupyter notebook which is not git compatible and have either 2 second latency of tab completion, no tab completion, no documentation on hover or useless documentation on hover, no way to easily redo the changes, no autosave, no error highlighting and possibility to use variable defined in a cell below in the cell above it
- lets use inconsistent variable names like "read_csv" and "isfile"
- lets pass a boolean variable as a string "true"
- lets contribute to tech enabled authoritarianism and create a face recognition and object detection models that china uses to destroy uyghur minority
- lets create a license plate computer vision system that will help government surveillance everyone, guys what a great idea

I don't want to deal with this bullshit language, bullshit ecosystem and bullshit unethical tech anymore.

Was training a model for an hour on paid GPU after which it showed a deprecation error and crashed my Jupyter notebook.

Pycharm could be a nice tool, if only it was not nagging about the professional version and the tools related to it so often. Shit can't even find the jupyter notebook crap. 🙄

NGL, open science feels like anarchy.

So the other day, I was working on some Python project when there was this bug that kept transforming. Like seriously, I would turn from "bool not defined" to "function does not exist" to literally "file does not exist"... within the FILE. And when I fixed them, new bugs kept popping up, and I couldn't find anything that was a problem. Nothing. There was this one function in there that, if I changed even the comments in there, would break. And so.... I turned off Atom and turned it on again. ( ha ) Didn't work. I restarted my computer. I copy pasted the file into another file. I used another IDE. I restarted GHCI. I restarted Jupyter Notebook... and after 6 hours... I found that it was because an if statement has a comparison between a bool and a bool, with a = in the middle. (not ==). I swear I almost threw the computer on the floor.

Just tried out Jupyter Notebook for the first time. I can see why software engineers wouldn't like notebooks, especially if you intend to actually publish the notebook as code for other people to use (please publish a module that can be imported, not a notebook that has to be hacked to pieces to make it reusable), but it's pretty handy for early prototyping or documentation.

I'm playing around with save-editing for a few GBA games as a personal project, and I used a Notebook to document the save file format with examples.

How long has GitHub been rendering Jupyter notebook files? That's slick.

I been doing a online course and they provide a exercise to do in Jupyter notebook.

I notice that the exercise they wanted us to do this time is too complex. After finishing the exercise I submit it for review.

I thought I am doing an exercise but I had actually done an assignment and submit it :(

Lucky I pass that assignment. It is the worst misunderstanding I have done during my student life.

Working with a data scientist on an update to a machine learning api that has dinner logic change with a new model.

He's wondering why his PRs are falling.

He's trying to merge into development from a branch created off of main.

He's renamed all the functions and classes and never updated the call points.

He's using new packages but never includes them in the requirements file, so the docket builds are failing.

His class method definitions don't contain self and are throwing syntax errors.

I've been working with him for 4 days to get him to understand branching, linting, unit testing, and not blindly copy and pasting snippets from jupyter notebook into production api code!

Random thoughts on more out of the box tools/environments.

Subject: Pharo

Some time ago I had shown one of my coworkers about Pharo and he quickly got the main idea behind it but mentioned how he didn't like the idea of leaving behind his text editor to deal with source code.

Some time last week I showed the dude some cool 3d animations you can do with Pharo while simultaneously manipulating the code to change them in real time. Now that caught his attention particularly and he decided he wanted to know more about the language but in particular the benefits of fucking around with an image based environment rather than a file based.

Both of us reached the conclusion that image based makes file based dev enviroments seem quaint in comparison, but estimated that it was nothing more than a sentiment rather than a fact.

We then considered what could be the advantage/disadvantages of such environments but I couldn't come up with anything other than the system not having something like Vim or VS Code or whatever which people love, but that it makes up for it with some of the craziest IDE tools I had ever seen. Plugins in this case act like source code repos that you can download and activate into your workflow in what feels something similar to VS Code being extended via plugins written in JS, and since the GUI is maleable as it is(because everything is basically just subsets of morp h windows) then extending functionality becomes so intuitive that its funny

Whereas with Emacs(for example) you have to really grind your gears with Elisp or Vimscript in Vim etc etc, with Pharo your plugin system is basicall you just adding classes that will convert your OS looking IDE into something else.

Because of how light the vm machine is, portability is a non issue, and passing pharo programs arround is not like installing Java in which you need the JVM.

Source code versioning, very important, already integrated into every live environment and can be extended to do pushes through simple key bindings with no hassle.

I dunno, I just feel that the tool is too good to be true. I keep trying to push limits into it but thus far I have found: data visualization and image modeling to work fine, web development with Teapot to be a cakewalk and work fine, therr are even packages for Arduino development.

I think its biggest con would be the image based system, but would really need to look into how this is bad by any reason other than "aww man I want vim!" since apparently some psychos already made Emacs and VS code packages for interfacing with Pharo source trees.

Embedded is certainly out of the question for any real project since its garbage collected and not the most performant cookie in the jar.

For Data science I can see some future, seems just as intuitive and interesting as a Jupyter Notebook actually, but the process can't and will not be the same since I still don't know of a way to save playground snippets unless you literally create classes for it, in which case every model you build gets saved inside of an object, sounds possible but, strange since it is not a the most common workflow in jupyter.

Some of the environment is sometimes glitchy, but it does have continuos development and have not found many hassles.

There is a biased factor from my side: I seem to be wired to understand the syntax and simple object model better than in other languages. To me this feels natural as if I was just writing ideas rather than code, mostly because I feel that there really ain't much in terms of syntax, the language gets out of my way and the IDE feels like the most intuitive environment in the world to me. I can see why some people would find it REALLY weird of counterintuitive tho.

Guess I really am a simple dude.

Today I was meeting with a researcher in my department so that I could show him how the software I developed works. He graduated from a really good university in electronic engineering, with 100/100 I think, and he can manage to copy&paste some python code. So I didn't expect what happened today.
Guy: 'So I have to give to your program as input this python file which contains a function you need to call, right?'
Me: 'Yep, I mean, that is a jupyter notebook, I need a text file containing only the function which is in that notebook'
Guy: *Downloads the notebook, tries to feed the notebook file into my program*
Me: 'Wait, don't, there probably is a lot of junk related to jupyter notebook, try opening it in notepad++'
Guy: *Opens file, sees a lot of junk text*
Me: 'Yeah, I thought so, you need to save it as plain text or .py'
Guy: *Renames the notebook as .txt*
Me: *Shakes my head without him noticing*
'That won't work, the content of the file won't change like that...'

Why the fuck isnt pythons tabbed loop thing something that's configurable?

So many things to like about python, but is there someone on this planet who actually likes this feature?

Trying to use it in Jupyter notebook (browser) is a nightmare, because tab will focus on next ui element.

Or am i missing something?

A jr dev was having an issue registering code with our data pipeline (prefect self hosted).

Turns out he's running vscode to launch a anaconda shell (didn't even know that was a thing) to launch jupyter notebook and running commands in the notebook (didn't know that was possible) all from Windows.

No it doesn't work. His environment configuration isn't right. I told him to just run Linux and get rid of all that nonsense.

Nothing is on git yet and were three weeks in! His code is full of hard coded absolute paths of files on his hard drive... He even had an example app to go buy, with a project layout to copy.

There's no helping some people

Rant:
My jupyter notebook has outgrown itself on some real world trading data analysis and its becoming a pain to add to (further) and share.
Need to find better alternatives, web apps where are you?

But i know nothing about it. Learning curve ahead!

Requirements:
I've 7 interactive dashboard plots (from some data) in jupyter-notebook.
- It'd be nicer to have a web app to use them without running notebook from a different location.
- Or running notebooks remotely (running as daemons on host machine).
Any suggestions for a starter ?
rant before requirements, coz rants lead to better requirements.

if rant++:
make_requirements(what_something)
do_work(that_something)

I just finished refactoring the code of a single jupyter notebook into a decent structure with comments. It feels good.
Unfortunately I still have stuff to implement and it's 2:50am :(

So… I’m in full stack bootcamp and don’t know much tricks of the trade as of yet… but, has anyone ever tried using “Jupyter-notebook” while using a libgit in a-Shell for iOS to edit cloned repository files from their phone?… it seems possible but I question its efficiency.

I have a deadline on 16th September. But AmazonWS has decided its not to cooperate. How, seriously, how do I copy my python files onto the stupid ec2 server and import them in the jupyter notebook.......

My younger bro started Coding today and the first thing he is asked me was if Jupyter Notebook has a dark mode or not.